Evidence map›Paper›PMID 26231170›Full record

ArticleBMC medical genomics2015

Loss of heterozygosity: what is it good for?

Georgina L Ryland, Maria A Doyle, David Goode, Samantha E Boyle, David Y H Choong, Simone M Rowley, Jason Li, Australian Ovarian Cancer Study Group, David D L Bowtell, Richard W Tothill and 2 more

Abstract read
In one paragraph

Article in BMC medical genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers.

0numbers the graph read from it
0cells of the map it votes in
65citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

65 citing papers in PubMed.

  1. Trial
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  11. Article
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  14. Article
  15. Review
  16. KaryoTap Enables Aneuploidy Detection in Thousands of Single Human Cells.bioRxiv : the preprint server for biology · 2024
    Article
  17. Article
  18. Article
  19. A Synopsis of Biomarkers in Glioblastoma: Past and Present.Current issues in molecular biology · 2024
    Review
  20. Article

5 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Georgina L RylandCancer Genetics Laboratory, Peter MacCallum Cancer Centre, East Melbourne, Victoria, Australia. georgina.ryland@petermac.org.
Maria A DoyleBioinformatics Core Facility, Peter MacCallum Cancer Centre, East Melbourne, Victoria, Australia. maria.doyle@petermac.org.
David GoodeBioinformatics and Cancer Genomics Laboratory, Peter MacCallum Cancer Centre, East Melbourne, Victoria, Australia. david.goode@petermac.org.
Samantha E BoyleCancer Genetics Laboratory, Peter MacCallum Cancer Centre, East Melbourne, Victoria, Australia. samantha.boyle@petermac.org.
David Y H ChoongCancer Genetics Laboratory, Peter MacCallum Cancer Centre, East Melbourne, Victoria, Australia. david.choong@petermac.org.
Simone M RowleyCancer Genetics Laboratory, Peter MacCallum Cancer Centre, East Melbourne, Victoria, Australia. simone.rowley@petermac.org.
Jason LiBioinformatics Core Facility, Peter MacCallum Cancer Centre, East Melbourne, Victoria, Australia. jason.li@petermac.org.
Australian Ovarian Cancer Study Group
David D L BowtellCancer Genomics and Genetics Laboratory, Peter MacCallum Cancer Centre, East Melbourne, Victoria, Australia. david.bowtell@petermac.org.
Richard W TothillMolecular Genomics Core Facility, Peter MacCallum Cancer Centre, East Melbourne, Victoria, Australia. richard.tothill@petermac.org.
Ian G CampbellCancer Genetics Laboratory, Peter MacCallum Cancer Centre, East Melbourne, Victoria, Australia. ian.campbell@petermac.org.
Kylie L GorringeCancer Genetics Laboratory, Peter MacCallum Cancer Centre, East Melbourne, Victoria, Australia. kylie.gorringe@petermac.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLoss of heterozygosity (LOH) is a common genetic event in cancer development, and is known to be involved in the somatic loss of wild-type alleles in many inherited cancer syndromes. The wider involvement of LOH in cancer is assumed to relate to unmasking a somatically mutated tumour suppressor gene through loss of the wild type allele.

methodsWe analysed 86 ovarian carcinomas for mutations in 980 genes selected on the basis of their location in common regions of LOH.

resultsWe identified 36 significantly mutated genes, but these could only partly account for the quanta of LOH in the samples. Using our own and TCGA data we then evaluated five possible models to explain the selection for non-random accumulation of LOH in ovarian cancer genomes: 1. Classic two-hit hypothesis: high frequency biallelic genetic inactivation of tumour suppressor genes. 2. Epigenetic two-hit hypothesis: biallelic inactivation through methylation and LOH. 3. Multiple alternate-gene biallelic inactivation: low frequency gene disruption. 4. Haplo-insufficiency: Single copy gene disruption. 5. Modified two-hit hypothesis: reduction to homozygosity of low penetrance germline predisposition alleles. We determined that while high-frequency biallelic gene inactivation under model 1 is rare, regions of LOH (particularly copy-number neutral LOH) are enriched for deleterious mutations and increased promoter methylation, while copy-number loss LOH regions are likely to contain under-expressed genes suggestive of haploinsufficiency. Reduction to homozygosity of cancer predisposition SNPs may also play a minor role.

conclusionIt is likely that selection for regions of LOH depends on its effect on multiple genes. Selection for copy number neutral LOH may better fit the classic two-hit model whereas selection for copy number loss may be attributed to its effect on multi-gene haploinsufficiency. LOH mapping alone is unlikely to be successful in identifying novel tumour suppressor genes; a combined approach may be more effective.

Indexed as

Loss of HeterozygosityFemaleGene DosageGenes, NeoplasmGenes, Tumor SuppressorGenomicsHaploinsufficiencyHumansOvarian Neoplasms

Identifiers

PMID26231170
PMCPMC4522148

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.